科学2026/09/22@ScienceDesk
Mendeleev Presents the Periodic Table
St. Petersburg State University, Менделеевская линия, округ № 7, Saint Petersburg, Northwestern Federal District, 199034, RussiaRussian Chemical Society
开始于 1869/03/06已确认可信度 85%157.6年前Wikipedia's^[2][3] Dmitri Mendeleev article states it plainly: "On 6 March 1869, he made a formal presentation to the Russian Chemical Society, titled The Dependence between the Properties of the Atomic Weights of the Elements". Russia was still on the Julian calendar, so contemporary Russian sources date the work to February; the manuscript sheet on Commons is signed 17.02.1869, the Julian date for 1 March, and the pin uses the Gregorian date Wikipedia gives for the presentation itself.
Dmitri Mendeleev's paper The Dependence between the Properties of the Atomic Weights of the Elements is read to the Russian Chemical Society in St Petersburg, arranging the known elements by atomic weight and valence and leaving gaps for elements not yet found.
0.63
AI2026/09/22@ScienceDesk
DeepMind Publishes the AlphaFold 2 Paper
DeepMind, Handyside Street, King's Cross, London Borough of Camden, Greater London, England, N1C 4BP, United KingdomDeepMind
开始于 2021/07/15已确认可信度 87%5.2年前Nature's^[1] own page for the article gives citation_online_date 2021/07/15 and shows "15 July 2021", and Wikipedia^[2][3] says the same: "On 15 July 2021, the AlphaFold 2 paper was published in Nature as an advance access publication alongside open source software and a searchable database of species proteomes." The print issue is dated August 2021.
Nature publishes Highly accurate protein structure prediction with AlphaFold, alongside open-source code and a database of predicted proteomes. Protein structure prediction stops being a bottleneck for drug discovery.
0.63
软件2026/09/22@ScienceDesk
Codd Publishes A Relational Model of Data for Large Shared Data Banks
IBM Almaden Research Center, 650, Harry Road, IBM Almaden Research Center, San Jose, Santa Clara County, California, 95120, United StatesIBM
开始于 1970/06/30预估可信度 75%56.2年前The paper's own header gives the issue and no day: Communications of the ACM, "Volume 13 / Number 6 / June, 1970". A month with no day is estimated at that month's last day.^[1]
Ted Codd's paper in Communications of the ACM proposes storing data as relations queried by predicate logic, independent of how it is laid out on disk. It is the founding document of the relational database and of SQL.
0.63
AI2026/09/23@TechDesk
NVIDIA Vera Rubin NVL72 Debuts in MLPerf Inference v6.1
NVIDIA…NVIDIA Endeavor, 2788 San Tomas Expressway, Santa Clara, California 95051, United States
开始于 2026/09/16 15:00已确认可信度 86%7天前MLCommons^[4] published the MLPerf Inference v6.1 results on 16 September 2026 - its GlobeNewswire release is datelined 'SAN FRANCISCO, Sept. 16, 2026' and stamped '11:00 AM EDT' - and NVIDIA's^[1][2] post of the same day says the results were 'released today'.
In its first peer-reviewed benchmark, NVIDIA's Vera Rubin NVL72 rack posted up to 3.7x the throughput of GB300 NVL72 on Qwen3-VL and 2.5x on DeepSeek-R1, submitted in the preview category of MLCommons' MLPerf Inference v6.1 round.
0.62
软件2026/09/23@TechDesk
英伟达推出面向容错量子计算的 CUDA-Q Logical
NVIDIA…Metro Toronto Convention Centre - North Building, Front Street West, Toronto, Ontario M5V 3H6, Canada
开始于 2026/09/14 13:00已确认可信度 84%9天前英伟达新闻室将发布日期标注为“2026年9月14日”（“英伟达今日宣布”），SiliconANGLE^[4] 当天09:00 EDT发布的报道也称“该消息是在本周于多伦多今日开幕的 IEEE Quantum Week 2026 上宣布的。”
这一为英伟达 CUDA-Q 新增的开源编排层，让研究人员可将纠错码、算法与量子比特硬件一同建模；费米实验室借此把容错设计工作从五个月缩短至三周。
0.62
半导体2026/09/23@TechDesk
TSMC's Second Kumamoto Fab (JASM) Starts 3nm Volume Production
TSMC…JASM, Haramizu, Kikuyo, Kikuchi County, Kumamoto Prefecture 869-1103, Japan
开始于 2028/12/31预估延期12个月可信度 71%2.3年后Only a year is given: Taiwan's MOEA says the fab is "scheduled to start installing equipment and come online in 2028", and C.C. Wei said on the 16 April 2026 call that "commercial production is scheduled to begin in 2028" - so the year's last day, estimated.^[1]
JASM's second fab in Kikuyo, Kumamoto - switched from 6nm-class chips to TSMC's 3nm process - is due to start volume production in 2028 at 15,000 12-inch wafers a month, making Japan's first 3nm chips about a year after the end-2027 start TSMC first promised.
$17B
0.61
AI2026/09/19@TechDesk
OpenAI 发布 o3-mini
OpenAI
开始于 2025/01/31 已确认可信度 92%1.6年前OpenAI^[1] 官方的模型发布说明将此条目的日期标注为 2025 年 1 月 31 日
OpenAI 发布 o3-mini，一款面向编程、数学和科学的高性价比推理模型，提供三档可调推理强度。
0.61
网络安全2026/09/22@ScienceDesk
Diffie and Hellman Publish New Directions in Cryptography
Stanford University, 450, Jane Stanford Way, Stanford, Santa Clara County, California, 94305, United StatesStanford University
开始于 1976/11/30预估可信度 75%49.8年前The paper's own running head gives the issue and no day: "IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. IT-22, NO. 6, NOVEMBER 1976". A month with no day is estimated at that month's last day.^[1]
Whitfield Diffie and Martin Hellman propose public-key cryptography and a way for two parties to agree a secret key over an open channel. It is the idea that later makes e-commerce and secure messaging possible.
0.61
机器人2026/09/21@TechDesk
NVIDIA Unveils the Isaac GR00T Reference Humanoid
NVIDIA…Taipei, Taiwan (NVIDIA GTC Taipei)
开始于 2026/06/01已确认可信度 85%114天前Happened as dated, per NVIDIA's^[1][3] release: "TAIPEI, Taiwan, June 01, 2026 (GLOBE NEWSWIRE) -- NVIDIA GTC Taipei -- NVIDIA today announced the NVIDIA Isaac GR00T Reference Humanoid Robot."
At GTC Taipei, NVIDIA announced the first open humanoid reference design: a Unitree H2 Plus chassis with Sharpa Wave five-finger tactile hands for the body, and Jetson Thor compute plus the open Isaac GR00T stack for the brain, aimed at academic robotics labs.
0.61
AI2026/09/19@TechDesk
GPT-5.1-Codex-Max 发布
OpenAI
开始于 2025/11/19 已确认可信度 90%308天前OpenAI^[1][2][3] 自家的模型发布说明将该条目的日期标注为 2025 年 11 月 19 日
OpenAI 发布 GPT-5.1-Codex-Max，这是一款前沿智能体编程模型，面向 Codex 中长时间运行的项目级任务。
0.61
AI2026/09/22@ScienceDesk
AlexNet Wins ImageNet and Starts the Deep Learning Boom
University of Toronto St. George, Chestnut Street, Yonge-Bay Corridor, University—Rosedale, Toronto, Golden Horseshoe, Ontario, M5G 1E2, CanadaUniversity of Toronto
开始于 2012/09/30已确认可信度 87%14年前Wikipedia's^[2][3] AlexNet article gives the submission date without hedging: "The three formed team SuperVision and submitted AlexNet in the ImageNet Large Scale Visual Recognition Challenge on September 30, 2012." The paper itself, "ImageNet Classification with Deep Convolutional Neural Networks", followed in Advances in Neural Information Processing Systems 25 later that year; the pin takes the dated competition result.
Alex Krizhevsky, Ilya Sutskever and Geoffrey Hinton submit a deep convolutional network to the ImageNet challenge as team SuperVision and win by a wide margin. The result turns GPU deep learning from a niche into an industry.
0.61
AI2026/09/19@TechDesk
OpenAI Releases Open-Weight gpt-oss-120b and gpt-oss-20b
OpenAI
开始于 2025/08/05 已确认可信度 88%1.1年前OpenAI's^[1][2] own model release notes date this entry August 5, 2025
OpenAI releases two open-weight reasoning models, gpt-oss-120b and gpt-oss-20b, for teams that want to run and customize models themselves.
0.60

Nature's^[1] own page for the article gives citation_online_date 1975/08/01 and shows "01 August 1975" as the publication date, with the paper received 14 May 1975 and accepted 26 June 1975; it is Nature volume 256, issue 5517, pages 495-497.

开始: 1975年8月1日可信度 90%来自来源

Köhler and Milstein Publish the Hybridoma Method

Georges Köhler and César Milstein report in Nature that fusing an antibody-producing cell with a myeloma cell yields a line that secretes a single antibody indefinitely. Monoclonal antibodies become the basis of the modern biologics industry.

"Continuous cultures of fused cells secreting antibody of predefined specificity" was published in Nature on 1 August 1975, volume 256, pages 495-497, received 14 May and accepted 26 June^[1]
Both authors were at the MRC Laboratory of Molecular Biology in Cambridge^[1]
The method makes identical antibodies of a single specificity, all descended from one parent cell and binding one epitope, in contrast to polyclonal mixtures from many plasma cell lineages^[2]
Köhler and Milstein shared the 1984 Nobel Prize in Physiology or Medicine with Niels Kaj Jerne "for theories concerning the specificity in development and control of the immune system and the discovery of the principle for production of monoclonal antibodies"^[3]

@ScienceDesk

参考资料 3可信度 88%

第一项始终是图钉的来源。总体可信度是各份资料对上方所用开始和结束时间支持程度的加权平均；资料每比最新的一份旧 180 天，权重减半。

[1]90%
nature.com/articles/256495a0
nature.com· 发布于 2026年9月22日· 开始 1975年8月1日 ✓· 占评分 33%
Nature's own page for the article gives citation_online_date 1975/08/01 and shows "01 August 1975" as the publication date, with the paper received 14 May 1975 and accepted 26 June 1975; it is Nature volume 256, issue 5517, pages 495-497.
[2]90%
Monoclonal antibody
en.wikipedia.org· 添加于 2026年9月22日· 占评分 33%
Defines what the method produces - "an antibody produced from a cell lineage made by cloning a unique white blood cell", all tracing back to a unique parent cell and binding a single epitope - against polyclonal mixtures.^[1]
[3]85%
Georges J. F. Köhler
en.wikipedia.org· 添加于 2026年9月22日· 占评分 33%
Records the paper - "In 1975 they published 'Continuous cultures of fused cells secreting antibody of predefined specificity' in Nature^[1]" - and the 1984 Nobel Prize in Physiology or Medicine shared with César Milstein and Niels Kaj Jerne.

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科学2026/09/22@ScienceDesk
Mendeleev Presents the Periodic Table
St. Petersburg State University, Менделеевская линия, округ № 7, Saint Petersburg, Northwestern Federal District, 199034, RussiaRussian Chemical Society
开始于 1869/03/06已确认可信度 85%157.6年前Wikipedia's^[2][3] Dmitri Mendeleev article states it plainly: "On 6 March 1869, he made a formal presentation to the Russian Chemical Society, titled The Dependence between the Properties of the Atomic Weights of the Elements". Russia was still on the Julian calendar, so contemporary Russian sources date the work to February; the manuscript sheet on Commons is signed 17.02.1869, the Julian date for 1 March, and the pin uses the Gregorian date Wikipedia gives for the presentation itself.
Dmitri Mendeleev's paper The Dependence between the Properties of the Atomic Weights of the Elements is read to the Russian Chemical Society in St Petersburg, arranging the known elements by atomic weight and valence and leaving gaps for elements not yet found.
0.63
AI2026/09/22@ScienceDesk
DeepMind Publishes the AlphaFold 2 Paper
DeepMind, Handyside Street, King's Cross, London Borough of Camden, Greater London, England, N1C 4BP, United KingdomDeepMind
开始于 2021/07/15已确认可信度 87%5.2年前Nature's^[1] own page for the article gives citation_online_date 2021/07/15 and shows "15 July 2021", and Wikipedia^[2][3] says the same: "On 15 July 2021, the AlphaFold 2 paper was published in Nature as an advance access publication alongside open source software and a searchable database of species proteomes." The print issue is dated August 2021.
Nature publishes Highly accurate protein structure prediction with AlphaFold, alongside open-source code and a database of predicted proteomes. Protein structure prediction stops being a bottleneck for drug discovery.
0.63
软件2026/09/22@ScienceDesk
Codd Publishes A Relational Model of Data for Large Shared Data Banks
IBM Almaden Research Center, 650, Harry Road, IBM Almaden Research Center, San Jose, Santa Clara County, California, 95120, United StatesIBM
开始于 1970/06/30预估可信度 75%56.2年前The paper's own header gives the issue and no day: Communications of the ACM, "Volume 13 / Number 6 / June, 1970". A month with no day is estimated at that month's last day.^[1]
Ted Codd's paper in Communications of the ACM proposes storing data as relations queried by predicate logic, independent of how it is laid out on disk. It is the founding document of the relational database and of SQL.
0.63
AI2026/09/23@TechDesk
NVIDIA Vera Rubin NVL72 Debuts in MLPerf Inference v6.1
NVIDIA…NVIDIA Endeavor, 2788 San Tomas Expressway, Santa Clara, California 95051, United States
开始于 2026/09/16 15:00已确认可信度 86%7天前MLCommons^[4] published the MLPerf Inference v6.1 results on 16 September 2026 - its GlobeNewswire release is datelined 'SAN FRANCISCO, Sept. 16, 2026' and stamped '11:00 AM EDT' - and NVIDIA's^[1][2] post of the same day says the results were 'released today'.
In its first peer-reviewed benchmark, NVIDIA's Vera Rubin NVL72 rack posted up to 3.7x the throughput of GB300 NVL72 on Qwen3-VL and 2.5x on DeepSeek-R1, submitted in the preview category of MLCommons' MLPerf Inference v6.1 round.
0.62
软件2026/09/23@TechDesk
英伟达推出面向容错量子计算的 CUDA-Q Logical
NVIDIA…Metro Toronto Convention Centre - North Building, Front Street West, Toronto, Ontario M5V 3H6, Canada
开始于 2026/09/14 13:00已确认可信度 84%9天前英伟达新闻室将发布日期标注为“2026年9月14日”（“英伟达今日宣布”），SiliconANGLE^[4] 当天09:00 EDT发布的报道也称“该消息是在本周于多伦多今日开幕的 IEEE Quantum Week 2026 上宣布的。”
这一为英伟达 CUDA-Q 新增的开源编排层，让研究人员可将纠错码、算法与量子比特硬件一同建模；费米实验室借此把容错设计工作从五个月缩短至三周。
0.62
半导体2026/09/23@TechDesk
TSMC's Second Kumamoto Fab (JASM) Starts 3nm Volume Production
TSMC…JASM, Haramizu, Kikuyo, Kikuchi County, Kumamoto Prefecture 869-1103, Japan
开始于 2028/12/31预估延期12个月可信度 71%2.3年后Only a year is given: Taiwan's MOEA says the fab is "scheduled to start installing equipment and come online in 2028", and C.C. Wei said on the 16 April 2026 call that "commercial production is scheduled to begin in 2028" - so the year's last day, estimated.^[1]
JASM's second fab in Kikuyo, Kumamoto - switched from 6nm-class chips to TSMC's 3nm process - is due to start volume production in 2028 at 15,000 12-inch wafers a month, making Japan's first 3nm chips about a year after the end-2027 start TSMC first promised.
$17B
0.61
AI2026/09/19@TechDesk
OpenAI 发布 o3-mini
OpenAI
开始于 2025/01/31 已确认可信度 92%1.6年前OpenAI^[1] 官方的模型发布说明将此条目的日期标注为 2025 年 1 月 31 日
OpenAI 发布 o3-mini，一款面向编程、数学和科学的高性价比推理模型，提供三档可调推理强度。
0.61
网络安全2026/09/22@ScienceDesk
Diffie and Hellman Publish New Directions in Cryptography
Stanford University, 450, Jane Stanford Way, Stanford, Santa Clara County, California, 94305, United StatesStanford University
开始于 1976/11/30预估可信度 75%49.8年前The paper's own running head gives the issue and no day: "IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. IT-22, NO. 6, NOVEMBER 1976". A month with no day is estimated at that month's last day.^[1]
Whitfield Diffie and Martin Hellman propose public-key cryptography and a way for two parties to agree a secret key over an open channel. It is the idea that later makes e-commerce and secure messaging possible.
0.61
机器人2026/09/21@TechDesk
NVIDIA Unveils the Isaac GR00T Reference Humanoid
NVIDIA…Taipei, Taiwan (NVIDIA GTC Taipei)
开始于 2026/06/01已确认可信度 85%114天前Happened as dated, per NVIDIA's^[1][3] release: "TAIPEI, Taiwan, June 01, 2026 (GLOBE NEWSWIRE) -- NVIDIA GTC Taipei -- NVIDIA today announced the NVIDIA Isaac GR00T Reference Humanoid Robot."
At GTC Taipei, NVIDIA announced the first open humanoid reference design: a Unitree H2 Plus chassis with Sharpa Wave five-finger tactile hands for the body, and Jetson Thor compute plus the open Isaac GR00T stack for the brain, aimed at academic robotics labs.
0.61
AI2026/09/19@TechDesk
GPT-5.1-Codex-Max 发布
OpenAI
开始于 2025/11/19 已确认可信度 90%308天前OpenAI^[1][2][3] 自家的模型发布说明将该条目的日期标注为 2025 年 11 月 19 日
OpenAI 发布 GPT-5.1-Codex-Max，这是一款前沿智能体编程模型，面向 Codex 中长时间运行的项目级任务。
0.61
AI2026/09/22@ScienceDesk
AlexNet Wins ImageNet and Starts the Deep Learning Boom
University of Toronto St. George, Chestnut Street, Yonge-Bay Corridor, University—Rosedale, Toronto, Golden Horseshoe, Ontario, M5G 1E2, CanadaUniversity of Toronto
开始于 2012/09/30已确认可信度 87%14年前Wikipedia's^[2][3] AlexNet article gives the submission date without hedging: "The three formed team SuperVision and submitted AlexNet in the ImageNet Large Scale Visual Recognition Challenge on September 30, 2012." The paper itself, "ImageNet Classification with Deep Convolutional Neural Networks", followed in Advances in Neural Information Processing Systems 25 later that year; the pin takes the dated competition result.
Alex Krizhevsky, Ilya Sutskever and Geoffrey Hinton submit a deep convolutional network to the ImageNet challenge as team SuperVision and win by a wide margin. The result turns GPU deep learning from a niche into an industry.
0.61
AI2026/09/19@TechDesk
OpenAI Releases Open-Weight gpt-oss-120b and gpt-oss-20b
OpenAI
开始于 2025/08/05 已确认可信度 88%1.1年前OpenAI's^[1][2] own model release notes date this entry August 5, 2025
OpenAI releases two open-weight reasoning models, gpt-oss-120b and gpt-oss-20b, for teams that want to run and customize models themselves.
0.60

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参考资料 3可信度 88%

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